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<Title>Boost Graph Library: Breadth-First Visit</Title>
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<H1><A NAME="sec:bfv"><img src="figs/python.gif" alt="(Python)"/>
<TT>breadth_first_visit</TT>
</H1>

<P>
<PRE>
  template &lt;class <a href="./IncidenceGraph.html">IncidenceGraph</a>, class P, class T, class R&gt;
  void breadth_first_visit(IncidenceGraph& G,
    typename graph_traits&lt;IncidenceGraph&gt;::vertex_descriptor s,
    const bgl_named_params&lt;P, T, R&gt;&amp; params);

  template &lt;class <a href="./IncidenceGraph.html">IncidenceGraph</a>, class <a href="./Buffer.html">Buffer</a>, class <a href="./BFSVisitor.html">BFSVisitor</a>, class ColorMap&gt;
  void breadth_first_visit
    (const IncidenceGraph&amp; g,
     typename graph_traits&lt;IncidenceGraph&gt;::vertex_descriptor s,
     Buffer&amp; Q, BFSVisitor vis, ColorMap color)
</PRE>

This function is basically the same as <tt>breadth_first_search()</tt>
except that the color markers are not initialized in the
algorithm. The user is responsible for making sure the color for every
vertex is white before calling the algorithm.  With this difference,
the graph type is only required to be an <a
href="./IncidenceGraph.html">Incidence Graph</a> instead of a <a
href="./VertexListGraph.html">Vertex List Graph</a>.  Also, this
difference allows for more flexibility in the color property map. For
example, one could use a map that only implements a partial function
on the vertices, which could be more space efficient when the search
only reaches a small portion of the graph.

<H3>Where Defined</H3>

<P>
<a href="../../../boost/graph/breadth_first_search.hpp"><TT>boost/graph/breadth_first_search.hpp</TT></a>


<h3>Parameters</h3>

IN: <tt>IncidenceGraph&amp; g</tt>
<blockquote>
  A directed or undirected graph. The graph type must
  be a model of <a href="./IncidenceGraph.html">Incidence Graph</a>.<br>

  <b>Python</b>: The parameter is named <tt>graph</tt>.
</blockquote>

IN: <tt>vertex_descriptor s</tt>
<blockquote>
  The source vertex where the search is started.<br>

  <b>Python</b>: The parameter is named <tt>root_vertex</tt>.
</blockquote>


<h3>Named Parameters</h3>

IN: <tt>visitor(BFSVisitor vis)</tt>
<blockquote>
  A visitor object that is invoked inside the algorithm at the
  event-points specified by the <a href="BFSVisitor.html">BFS
  Visitor</a> concept. The visitor object is passed by value <a
  href="#1">[1]</a>.<br> <b>Default:</b>
  <tt>bfs_visitor&lt;null_visitor&gt;</tt><br>

  <b>Python</b>: The parameter should be an object that derives from
  the <a href="BFSVisitor.html#python"><tt>BFSVisitor</tt></a> type of the graph.
</blockquote>

UTIL/OUT: <tt>color_map(ColorMap color)</tt>
<blockquote>
  This is used by the algorithm to keep track of its progress through
  the graph. The type <tt>ColorMap</tt> must be a model of <a
  href="../../property_map/doc/ReadWritePropertyMap.html">Read/Write
  Property Map</a> and its key type must be the graph's vertex
  descriptor type and the value type of the color map must model
  <a href="./ColorValue.html">ColorValue</a>.<br>
  <b>Default:</b> <tt>get(vertex_color, g)</tt><br>

  <b>Python</b>: The color map must be a <tt>vertex_color_map</tt> for
  the graph.
</blockquote>

UTIL: <tt>buffer(Buffer&amp; Q)</tt>
<blockquote>
  The queue used to determine the order in which vertices will be
  discovered.  If a FIFO queue is used, then the traversal will
  be according to the usual BFS ordering. Other types of queues
  can be used, but the traversal order will be different.
  For example Dijkstra's algorithm can be implemented
  using a priority queue. The type <tt>Buffer</tt> must be a model of
  <a href="./Buffer.html">Buffer</a>.<br>
  <b>Default:</b> <tt>boost::queue</tt><br>

  <b>Python</b>: The buffer must derive from the <a
  href="./Buffer.html">Buffer</a> type for the graph.
</blockquote>


<H3><A NAME="SECTION001330300000000000000">
Complexity</A>
</H3>

<P>
The time complexity is <i>O(E)</i>.

<P>

<h3>Visitor Event Points</h3>

<ul>
<li><b><tt>vis.examine_vertex(u, g)</tt></b>r is invoked in each
  vertex as it is removed from the queue.

<li><b><tt>vis.examine_edge(e, g)</tt></b> is invoked on every out-edge
  of each vertex immediately after the vertex is removed from the queue.

<li><b><tt>vis.tree_edge(e, g)</tt></b> is invoked (in addition to
  <tt>examine_edge()</tt>) if the edge is a tree edge. The
  target vertex of edge <tt>e</tt> is discovered at this time.

<li><b><tt>vis.discover_vertex(u, g)</tt></b> is invoked the first time the
  algorithm encounters vertex <i>u</i>. All vertices closer to the
  source vertex have been discovered, and vertices further from the
  source have not yet been discovered.

<li><b><tt>vis.non_tree_edge(e, g)</tt></b> is invoked (in addition to
  <tt>examine_edge()</tt>) if the edge is not a tree edge.

<li><b><tt>vis.gray_target(e, g)</tt></b> is invoked (in addition to
  <tt>non_tree_edge()</tt>) if the target vertex is colored gray at the
  time of examination. The color gray indicates that
  the vertex is currently in the queue.

<li><b><tt>vis.black_target(e, g)</tt></b> is invoked (in addition to
  <tt>non_tree_edge()</tt>) if the target vertex is colored black at the
  time of examination. The color black indicates that the
  vertex is no longer in the queue.

<li><b><tt>vis.finish_vertex(u, g)</tt></b> is invoked after all of the out
  edges of <i>u</i> have been examined and all of the adjacent vertices
  have been discovered.

</ul>

<h3>See Also</h3>

<a href="./breadth_first_search.html"><tt>breadth_first_search()</tt></a>,
<a href="./bfs_visitor.html"><tt>bfs_visitor</tt></a>, and
<a href="./depth_first_search.html"><tt>depth_first_search()</tt></a>

<h3>Notes</h3>

<p><a name="1">[1]</a>
  Since the visitor parameter is passed by value, if your visitor
  contains state then any changes to the state during the algorithm
  will be made to a copy of the visitor object, not the visitor object
  passed in. Therefore you may want the visitor to hold this state by
  pointer or reference.

<br>
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<TD nowrap>Copyright &copy; 2000-2001</TD><TD>
<A HREF="http://www.boost.org/people/jeremy_siek.htm">Jeremy Siek</A>, Indiana University (<A HREF="mailto:jsiek@osl.iu.edu">jsiek@osl.iu.edu</A>)
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